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AI at the Edge: TensorFlow to TensorRT on Jetson

Deep neural networks developed with TensorFlow can be deployed on NVIDIA Jetson and accelerated up to 5x with TensorRT. This webinar covers the conversion of pretrained TensorFlow image detection models to TensorRT for deployment on the Jetson TX2 platform.

By attending this webinar, you'll learn:
  1. How TensorFlow performance compares with TensorRT using popular models like Inception and MobileNet
  2. System setup for running TensorFlow and TensorRT on the Jetson
  3. How to inspect a TensorFlow graph for TensorRT compatibility
  4. Workflows for converting TensorFlow image classification models to TensorRT
  5. How to execute TensorRT image classification models on the Jetson TX2
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Presented By
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John Welsh
Developer Technology Engineer, NVIDIA

John Welsh is a developer technology engineer of autonomous machines at NVIDIA, where he develops accelerated applications with NVIDIA Jetson. Whether it’s Legos, robots or a song on a guitar, he always enjoys creating new things. John holds a Bachelor of Science and Master of Science in electrical engineering from the University of Maryland, focusing on robotics and computer vision.
 
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